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CO 2 and NO x emissions from aviation transportation are critical components of overall transportation-related emissions, significantly impacting both climate and air quality. To implement more targeted and effective measures for mitigating emissions in this sector, it is essential to conduct empirical analyses that deepen our understanding of the factors influencing aviation emissions. Previous studies have predominantly focused on emissions from the entire transportation sector, with limited research specifically addressing aviation emissions. Notably, past research has often overlooked the existence of spatial autocorrelation patterns in aviation emissions. Here, we developed a civil aviation emission inventory at the provincial scale for China using a bottom-up approach based on daily flight schedules from 2012 to 2019. By utilizing the STIRPAT and spatial Durbin models, we identified key factors affecting civil aviation CO 2 and NO x emissions and assessed their spatial effects at the provincial level in China. Spatial-temporal analysis revealed distinct patterns and spatial non-stationarity in CO 2 and NO x emissions from civil aviation. The results also highlighted that GDP, per capita GDP, the transportation price index, and per capita consumption expenditure positively drive. The results emphasize the importance of close collaboration among different provinces to effectively decarbonize and reduce pollution in the civil aviation sector given the significant observed spatial dependencies. These findings provide valuable insights for policymakers in formulating strategies to reduce aviation emissions and understanding the influence of different socioeconomic activities on emissions. [Display omitted] • An emission inventory for civil aviation in China from 2012 to 2019 is established. • A STIRPAT and spatial Durbin model are applied to assess key driving factor's impact. • A clustering or agglomeration effect is observed in China's aviation emissions. • Economic factors correlate positively emissions, transportation structure negatively. • Spatial dependence exists, emphasizing the need for collaboration to cut emissions. [ABSTRACT FROM AUTHOR]

Local land-sea breezes play an important role in coastal air quality because they circulate air between coastal/urban and marine areas, potentially causing the accumulation of pollutants. This has been observed for the secondary photochemical pollutant ozone. However, particulate matter (PM) also warrants investigation. To understand the complicated interactions between coastal urban air quality and a local land-sea breeze, we analyzed historical monitoring data from Houston, Texas, which is the fourth most populous city in the United States. Using k-means clustering algorithms to analyze wind data from Houston, we successfully identified a sea breeze recirculation cluster. Additionally, we performed positive matrix factorization on PM 2.5 (2.5 μm in diameter or smaller) composition data for 2010–2018 from Houston Deer Park #2 monitoring site, 5 km south of the industrialized Houston Ship Channel. The resulting eight factors indicated a variety of anthropogenic, natural, primary and secondary sources. Emphasizing the PM 2.5 sources in each of the wind clusters for June, July, and August, we discovered that on southernly wind and sea breeze recirculation days, the PM 2.5 concentrations are ∼30% higher than those under other wind patterns. Under southerly wind, 53% of PM 2.5 was attributed to long-range transport of soil and 15% to aged and fresh sea salt. In contrast, on days identified as being impacted by a sea breeze, 60% of PM 2.5 was attributed to anthropogenic emissions and only 15% to soil sources. Secondary organic aerosol from multiple sources also appeared to be important on sea breeze days. [Display omitted] [ABSTRACT FROM AUTHOR]

Prior studies reported excess rates (ERs) of cardiorespiratory events associated with short-term increases in PM 2.5 concentrations, despite implementation of pollution-control policies. In 2017, Federal Tier 3 light-duty vehicle regulations began, and to-date there have been no assessments of population health effects of the policy. Using the NYS Statewide Planning and Research Cooperative System (SPARCS) database, we obtained hospitalizations and ED visits with a principal diagnosis of asthma or chronic obstructive pulmonary disease (COPD) for residents living within 15 miles of six urban PM 2.5 monitoring sites in NYS (2014–2019). We used a time-stratified case-crossover design and conditional logistic regression (adjusting for ambient temperature, relative humidity, and weekday) to estimate associations between PM 2.5 , POC (primary organic carbon), SOC (secondary organic carbon), and rates of respiratory disease hospitalizations and emergency department (ED) visits from 2014 to 2019. We evaluated demographic disparities in these relative rates and compared changes in ERs before (2014–2016) and after Tier 3 implementation (2017–2019). Each interquartile range increase in PM 2.5 was associated with increased ERs of asthma or COPD hospitalizations and ED visits in the previous 7 days (ERs ranged from 1.1%–3.1%). Interquartile range increases in POC were associated with increased rates of asthma ED visits (lag days 0–6: ER = 2.1%, 95% CI = 0.7%, 3.6%). Unexpectedly, the ERs of asthma admission and ED visits associated with PM 2.5 , POC, and SOC were higher during 2017–2019 (after Tier 3) than 2014–2016 (before Tier-3). Chronic obstructive pulmonary disease analyses showed similar patterns. Excess Rates were higher in children (<18 years; asthma) and seniors (≥65 years; COPD), and Black, Hispanic, and NYC residents. In summary, unanticipated increases in asthma and COPD ERs after Tier-3 implementation were observed, and demographic disparities in asthma/COPD and PM2.5, POC, and SOC associations were also observed. Future work should confirm findings and investigate triggering of respiratory events by source-specific PM. [Display omitted] • PM2.5 was associated with increased asthma and COPD admissions and ED visits. • PM2.5's respiratory effect occurred immediately and lasted for entire week. • Higher Asthma ED visits and COPD admissions were associated with POC and SOC. • 2-4-fold increase in exposure-health associations after policies implemented. • Children, seniors, minority, and NYC residents were more vulnerable to pollutants. [ABSTRACT FROM AUTHOR]

Per- and polyfluoroalkyl substances (PFAS) are a group of synthetic chemicals detected throughout the environment. To better understand the distribution of PFAS in an aquatic system (the Laurentian Great Lakes), stable isotope enrichment (δ13C and δ15N), fatty acid (FA) profiles, and PFAS were measured in various species from the Lake Ontario (LO) aquatic food web. Sampled organisms included top predator fish, prey fish, and benthic and pelagic macroinvertebrates. The trophic level of each species in the LO food web was determined using δ15N, and FA concentrations (range: <1–139 mg/g wet weight (ww)). The individual PFAS concentrations in the LO food web were ~1.5 to 5 times lower than previously reported. The highest PFAS concentrations were observed in deepwater sculpin (Myoxocephalus thompsonii , 150 ± 35.7 ng/g ww) suggesting a potential source of PFAS from the offshore benthic zone or sediment. The concentration of PFOS and long chain (C9-C14) perfluoroalkyl carboxylic acids (PFCAs) were significantly higher than short chain PFAS indicating the significant impact of hydrophobicity on the bioaccumulation of PFAS in organisms from the food web. However, high molecular weight PFCAs (>C8) did not exhibit increasing biomagnification factors (BMFs) and trophic magnification factors (TMFs) with log K ow , suggesting hydrophobicity does not govern the movement of PFAS from low to high trophic levels in the LO food web. [ABSTRACT FROM AUTHOR]

Acadia National Park (ANP) is located on Mt. Desert Island, ME on the U.S. Atlantic coast. ANP is routinely a top-ten most popular National Park with over four million visits in 2022. The overall contribution and negative effects of long-range atmospheric transport and local sources of dioxin-like contaminants endangering natural and wildlife resources is unknown. Dioxin-like (DL) contaminants polychlorinated dibenzo-p-dioxins (∑PCDD) and polychlorinated dibenzofurans (∑PCDF), non-ortho coplanar PCBs (∑CP4), and polychlorinated naphthalenes (∑PCNs) were measured at the McFarland Hill air monitoring station (44.37⁰N, 68.26⁰W). On a mass/volume basis, total PCNs averaged 90.9 % (788 fg/m3) of DL contaminants measured annually, with 92.9 % of the collected total in the vapor-phase. Alternatively, total dioxin/furans (∑PCDD/Fs) represented 71.6 % of the total toxic equivalence (∑TEQ) (1.018 fg-TEQ/m3), with 69.7 % in the particulate-phase. Maximum concentrations measured for individual sampling events for ∑PCDD/F, ∑CP4, and ∑PCN were 159 (winter), 139 (summer), and 2100 (autumn), fg/m3 respectively. Whereas the maximum ∑TEQ concentrations for individual sampling events for ∑PCDD/F, ∑CP4, and ∑PCN were 2.8 (autumn), 0.38 (summer), and 0.71 (autumn), fg-TEQ/m3 respectively. Pearson correlations were calculated for ∑PCDD/Fs and ∑PCN particulate/vapor-phase air concentrations and PM 2.5 wood smoke "indicator" species. The most significant correlations were observed in autumn for particulate-phase ∑PCDD/Fs suggesting a relationship between visitation-generated combustion sources (campfires and/or waste burning) or climate-change mediated forest fires. Significant Clausius-Clapeyron (C–C) correlations observed for particulate-phase ∑PCDDs (r2 = 0.567) as ambient temperatures decreased suggests a connection between localized domestic heating sources or visitor-based burning of wood/trash resources. Alternatively, highly significant C–C vapor-phase ∑CP4-PCBs correlations (r2 = 0.815) implies that the majority of ∑CP4-PCB loading to ANP is from long-range atmospheric transport processes. Based on these findings, Acadia National Park should be classified as a remote site with minor depositional impacts from ∑PCDD/Fs, ∑CP4-PCBs, and ∑PCN atmospheric transport or local diffuse sources. [Display omitted] • Thermal combustion sources are important contributors to contaminant deposition. • Depositional pathways are due to both air-surface exchange and combustion byproducts. • Wood smoke indicator particulates, PCDD/Fs, and PCNs were seasonally correlated. • Forest fires and visitor biomass combustion likely contribute to contaminant deposition. [ABSTRACT FROM AUTHOR]

This study assessed the spatial variability of PM 2.5 source contributions across ten sites located in the South Coast Air Basin, California. Eight pollution sources and their contributions were obtained using positive matrix factorization (PMF) from the PM 2.5 compositional data collected during the two sampling campaigns (2012/13 and 2018/19) of the Multiple Air Toxics Exposure Study (MATES). The identified sources were "gasoline vehicles", "aged sea salt", "biomass burning", "secondary nitrate", "secondary sulfate", "diesel vehicles", "soil/road dust" and "OP-rich". Among them, "gasoline vehicle" was the largest contributor to the PM 2.5 mass. The spatial distributions of source contributions to PM 2.5 at the sites were characterized by the Pearson correlation coefficients as well as coefficients of determination and divergence. The highest spatial variability was found for the contributions from the "OP-rich" source in both MATES campaigns suggesting varying influences of the wildfires in the Los Angeles Basin. Alternatively, the smallest spatial variabilities were observed for the contributions of the "secondary sulfate" and "aged sea salt" sources resolved for the MATES campaign in 2012/13. The "soil/road dust" contributions of the sites from the 2018/19 campaign were also highly correlated. Compared to the other sites, the source contribution patterns observed for Inland Valley and Rubidoux were the most diverse from the others likely due to their remote locations from the other sites, the major urban area, and the Pacific Ocean. [Display omitted] • This study represents the largest area, multiple site source analysis done to date. • Pollution sources in 2012/13 and 2018/19 at 10 sites in SoCAB were identified. • OP-rich contributions were the most variable due to the influence of wildfires. • Secondary sulfate (SS) contributions were least variable during 2012/13. • "Gasoline vehicles" and SS contributed most to the PM 2.5 change between campaigns. [ABSTRACT FROM AUTHOR]

East Asian countries have been conducting source apportionment of fine particulate matter (PM 2.5) by applying positive matrix factorization (PMF) to hourly constituent concentrations. However, some of the constituent data from the supersites in South Korea was missing due to instrument maintenance and calibration. Conventional preprocessing of missing values, such as exclusion or median replacement, causes biases in the estimated source contributions by changing the PMF input. Machine learning (ML) can estimate the missing values by training on constituent data, meteorological data, and gaseous pollutants. Complete data from the Seoul Supersite in 2018 was taken, and a random 20% was set as missing. PMF was performed by replacing missing values with estimates. Percent errors of the source contributions were calculated compared to those estimated from complete data. Missing values were estimated using a random forest analysis. Estimation accuracy (r2) was as high as 0.874 for missing carbon species and low at 0.631 when ionic species and trace elements were missing. For the seven highest contributing sources, replacing the missing values of carbon species with estimates minimized the percent errors to 2.0% on average. However, replacing the missing values of the other chemical species with estimates increased the percent errors to more than 9.7% on average. Percent errors were maximal at 37% on average when missing values of ionic species and trace elements were replaced with estimates. Missing values, except for carbon species, need to be excluded. This approach reduced the percent errors to 7.4% on average, which was lower than those due to median replacement. Our results show that reducing the biases in source apportionment is possible by replacing the missing values of carbon species with estimates. To improve the biases due to missing values of the other chemical species, the estimation accuracy of the ML needs to be improved. [Display omitted] • Missing values of hourly PM 2.5 constituents were estimated using a random forest. • Estimation accuracy (r2) was 0.631–0.874, highest for carbon species. • PMF was performed by replacing missing values in the input data with estimates. • Source contributions were compared to the complete PMF result with percent errors. • Replacing the missing carbon species minimized the percent errors to 2.0%. [ABSTRACT FROM AUTHOR]

During the cold season in South Korea, NO 3 − concentrations are known to significantly increase, often causing PM 2.5 to exceed air quality standards. This study investigated the formation mechanisms of NO 3 − in a suburban area with low anthropogenic emissions. The average PM 2.5 was 25.3 μg m−3, with NO 3 − identified as the largest contributor. Ammonium-rich conditions prevailed throughout the study period, coupled with low atmospheric temperature facilitating the transfer of gaseous HNO 3 into the particulate phase. This result indicates that the formation of HNO 3 played a crucial role in determining particulate NO 3 − concentration. Nocturnal increases in NO 3 − were observed alongside increasing ozone (O 3) and relative humidity (RH), emphasizing the significance of heterogeneous reactions involving N 2 O 5. NO 3 − concentrations at the study site were notably higher than in Seoul, the upwind metropolitan area, during a high concentration episode. This difference could potentially attributed to lower local NO concentrations, which enhanced the reaction between O 3 and NO 2 , to produce NO 3 radicals. High concentrations of Cl− and dust were also identified as contributors to the elevated NO 3 − concentrations. [Display omitted] • Nitrate (NO 3 −) spikes led to PM 2.5 exceedances in low-emission suburban area. • Nocturnal NO 3 − rises were linked to increased O 3 and relative humidity (RH). • A substantial increase of NO 3 − was observed around the deliquescence RH of NH 4 NO 3. • High concentrations of Cl− and dust also contributed to active NO 3 − formation. [ABSTRACT FROM AUTHOR]

During the past two decades, efforts have been made to further reduce particulate air pollution across New York State through various Federal and State policy implementations. Air quality has also been affected by economic drivers like the 2007–2009 recession and changing costs for different approaches to electricity generation. Prior work has focused on particulate matter with aerodynamic diameter ≤2.5 μm. However, there is also interest in the effects of ultrafine particles on health and the environment and analyses of changes in particle number concentrations (PNCs) are also of interest to assess the impacts of changing emissions. Particle number size distributions have been measured since 2005. Prior apportionments have been limited to seasonal analyses over a limited number of years because of software limitations. Thus, it has not been possible to perform trend analyses on the source-specific PNCs. Recent development have now permitted the analysis of larger data sets using Positive Matrix Factorization (PMF) including its diagnostics. Thus, this study separated and analyzed the hourly averaged size distributions from 2005 to 2019 into two data sets; October to March and April to September. Six factors were resolved for both data sets with sources identified as nucleation, traffic 1, traffic 2, fresh secondary inorganic aerosol (SIA), aged SIA, and O3-rich aerosol. The resulting source-specific PNCs were combined to provide continuous data sets and analyzed for trends. The trends were then examined with respect to the implementation of regulations and the timing of economic drivers. Nucleation was strongly reduced by the requirement of ultralow (<15 ppm) sulfur on-road diesel fuel in 2006. Secondary inorganic particles and O 3 -rich PNCs show strong summer peaks. Aged SIA was constant and then declined substantially in 2015 but rose in 2019. Traffic 1 and 2 have steadily declined bur rose in 2019. [Display omitted] • Particle number size distributions (PNSDs) measured in Rochester NY from 2005-19. • Source analysis of PNSDs performed using Positive Matrix Factorization (PMF). • Sources were Nucleation, Traffic 1 & 2, Fresh and Aged SIA, & O 3 -rich. • Trend analyses performed for each source particle number concentrations. • Traffic and Nucleation initially declined; all sources rose in recent years. [ABSTRACT FROM AUTHOR]

Hexavalent chromium (Cr(VI)) is a known carcinogen derived from both anthropogenic and natural sources. This work reports the size-segregated concentrations of total Cr(VI) in particulate matter (PM) in Astana, the capital of Kazakhstan, and provides new insights into the gas-solid reactions of atmospheric Cr. A study of total Cr(VI) in the particulate matter, via a microwave-assisted digestion technique, was conducted using a 5-stage Sioutas Cascade impactor that captures airborne particles in size ranges: >2.5 μm, 1.0–2.5 μm, 0.50–1.0 μm, 0.25–0.50 μm, and <0.25 μm. The total Cr(VI) concentration in the size fraction <0.25 μm was the highest with a maximum value of 9.7 ng/m3. This high concentration may pose a greater risk because smaller airborne particles can penetrate deeper into the lower respiratory tract of the lungs. Total suspended particles Cr(VI) exceeded the 8.0 ng/m3 Reference Concentration (RfC) by 22 times. The overall total Cr(VI) concentration in summer was significantly higher than in fall (p < 0.05), which could be due to factors, including higher temperatures, ozone, and NO 2 concentrations in summer and a higher VOC concentration in fall. The results indicate that the interaction between Cr(III) and Cr(VI) through gas-solid reaction can control the speciation of atmospheric Cr. • Total Cr(VI) sizing in PM helps to know the extent of particle entry into the body. • Cr(VI) < 0.25 μm is riskier since particles can penetrate deeper into the lungs. • Gas-solid reaction controls Cr chemistry, causing Cr(III)–Cr(VI) interconversion. • Higher temperature and O 3 in summer increases the concentration of total Cr(VI). [ABSTRACT FROM AUTHOR]

PM 2.5 was sampled over a seven-year period (2013–2019) at two locations ∼50 km apart in Southern Ontario (concurrently for five years: 2015–2019). One is a heavily industrialized site (Hamilton), while the other was a rural site (Simcoe). To assess the impact of industrialization on the composition and sources of PM affecting air quality in these two locations, positive matrix factorization coupled with dispersion normalization (DN-PMF) was used to identify six and eight factors at Simcoe and Hamilton, respectively. The Simcoe factors in order of diminishing PM mass contribution were: particulate sulphate (pSO4), secondary organic aerosol (SOA), crustal matter, particulate nitrate (pNO3), biomass burning, and vehicular emissions. At Hamilton, the effects of industrialization were observed by the ∼36% higher average ambient PM 2.5 concentration for the study period as well as the presence of factors unique to metallurgy, i.e., coking and steelmaking, compared to Simcoe. The coking and steelmaking factors contributed ∼15% to the PM mass at Hamilton. Seasonal variants of appropriate nonparametric trend tests with the associated slopes (Sen's) were used to assess statistically significant changes in the factor contributions to PM 2.5 over time. Specifically at Hamilton, a significant decline in PM contributions was noted for coking (−0.03 μg/m³/yr or −4.1%/yr) while steelmaking showed no statistically significant decline over the study period. Other factors at Hamilton that showed statistically significant declines over the study period were: pSO4 (−0.27 μg/m³/yr or −12.6%/yr), biomass burning (−0.05 μg/m³/yr or −9.02%/yr), crustal matter (−0.03 μg/m³/yr or −5.28%/yr). These factors mainly accounted for the significant decline in PM 2.5 over the study period (−0.35 μg/m³/yr or −4.24%/yr). This work shows the importance of long-term monitoring in assessing the unique contributions and temporal changes of industrialization on air quality in Ontario and similarly affected locations. [Display omitted] • DN-PMF applied to 24-hr integrated PM 2.5 data from 2 close locations in Ontario. • 8 factors found in Hamilton, a heavily industrialized city, 6 the same as at Simcoe. • Coking & steelmaking factors were additionally found in Hamilton but not at Simcoe. • Trends tests showed significant declines in particulate sulphate at both locations. • In Hamilton, industrial factors had most PM 2.5 heavy metals and elemental species. [ABSTRACT FROM AUTHOR]

Epidemiological studies have documented that exposure to fine particulate matter (PM 2.5) could affect neurodevelopment, thereby leading to autism spectrum disorders (ASD). Nevertheless, there is little laboratory data to support this epidemiological evidence. In the current study, we carried out a series of experiments to assess whether developmental exposures to different extracts of PM 2.5 can result in ASD-like behavioral, biochemical, and immunohistochemical characteristics in male rat offspring. PM 2.5 samples were collected daily for a year, and monthly composites were extracted with an acetone-hexane mixture. The extracts were analyzed for their chemical constituents. Three groups of rats were exposed to the different PM 2.5 extracts during pre- and postnatal periods. All exposed groups of rats exhibited typical behavioral features of ASD, including increased repetitive and depression-related behaviors. We also found microglia and astrocytes activation and decreased concentrations of oxytocin (OXT) in the brain regions of exposed rats compared with control rats. Comparing the current results with a prior study, the induced biological effects followed a sequence of whole particles of PM 2.5 > organic extract > inorganic extract. These findings indicated that exposure to PM 2.5 can elicit ASD-like features in rats and raise concerns about particulate matter as a possible trigger for the induction of ASD in humans; therefore, mitigating the contents of the PAHs and metals could reduce the PM 2.5 neurotoxicity. [Display omitted] • Pre- and postnatal exposure to PM 2.5 extracts caused autism-like behavior in rats. • Exposure to PM 2.5 extracts induced the activation of glial cells in rats. • PM 2.5 exposure reduced oxytocin levels in the brain regions and plasma of rats. [ABSTRACT FROM AUTHOR]

A long-term (2013–2019) PM 2.5 speciation dataset measured in Tianjin, the largest industrial city in northern China, was analyzed with dispersion normalized positive matrix factorization (DN-PMF). The trends of source apportioned PM 2.5 were used to assess the effectiveness of source-specific control policies and measures in support of the two China's Clean Air Actions implemented nationwide in 2013–2017 and 2018–2020, respectively. Eight sources were resolved from the DN-PMF analysis: coal combustion (CC), biomass burning (BB), vehicular emissions, dust, steelmaking and galvanizing emissions, a mixed sulfate-rich factor and secondary nitrate. After adjustment for meteorological fluctuations, a substantial improvement in PM 2.5 air quality was observed in Tianjin with decreases in PM 2.5 at an annual rate of 6.6%/y. PM 2.5 from CC decreased by 4.1%/y. The reductions in SO 2 concentration, PM 2.5 contributed by CC, and sulfate demonstrated the improved control of CC-related emissions and fuel quality. Policies aimed at eliminating winter-heating pollution have had substantial success as shown by reduced heating-related SO 2 , CC, and sulfate from 2013 to 2019. The two industrial source types showed sharp drops after the 2013 mandated controls went into effect to phaseout outdated iron/steel production and enforce tighter emission standards for these industries. BB reduced significantly by 2016 and remained low due to the no open field burning policy. Vehicular emissions and road/soil dust declined over the Action's first phase followed by positive upward trends, showing that further emission controls are needed. Nitrate concentrations remained constant although NO X emissions dropped significantly. The lack of a decrease in nitrate may result from increased ammonia emissions from enhanced vehicular NO X controls. The port and shipping emissions were evident implying their impacts on coastal air quality. These results affirm the effectiveness of the Clean Air Actions in reducing primary anthropogenic emissions. However, further emission reductions are needed to meet global health-based air quality standards. [Display omitted] • Trends of source apportioned PM 2.5 were analyzed with 1894 filter samples. • Reductions in primary anthropogenic emissions notably lowered PM 2.5 concentration. • Nitrate remained constant although NO X emissions dropped significantly. • Port and shipping emissions were evident in Tianjin. [ABSTRACT FROM AUTHOR]

Biomass-burning emissions are a significant source of primary organic aerosol (POA). Volatility is one of the most important physical properties of organic aerosol (OA). Dilution and thermodenuder (TD) measurements were used to investigate the volatility of POA from household crop waste combustion in China. Between 10% and 30% of the POA desorbed when diluted from 20:1 to 120:1, while 10%–40% of POA evaporated in the TD when heated to 150 °C. Thus, a considerable proportion of the POA emissions were volatile. A dynamic mass transfer model was applied to derived volatility distributions of POA based on TD data. A best fit volatility distributions for POA and associated mass accommodation coefficients (α), and the enthalpy of vaporization (ΔH vap) were presented. The emissions factors and volatility distribution of POA emission from household crop waste combustion in this study can be used to improve emission inventories and simulate gas-particle partitioning of organic aerosol in chemical transport models. [Display omitted] • Volatility of primary organic aerosol from biomass combustion was investigated. • Primary organic aerosol emissions were affected by dilution ratio. • 10%–40% of primary organic aerosol evaporated when heated. • A considerable proportion of primary organic aerosol were volatile. • A best fit volatility distributions for primary organic aerosol were determined. [ABSTRACT FROM AUTHOR]

Ambient fine particulate matter (PM 2.5) data were collected in the lower City of Hamilton, Ontario to apportion the sources of this pollutant over an 18-month period. Hamilton has complex topographical features that may result in worsened air pollution within the lower city, thus, dispersion-normalized, multi-time resolution factor analysis (DN-MT-FA) was used to identify and quantify contributions of factors in a manner that reduced the influence of local meteorology. These factors were secondary organic aerosols type 1 (SOA_1), particulate nitrate (pNO3), particulate sulphate (pSO4), primary traffic organic matter (PTOM), Steel/metal processing and vehicular road dust emissions (Steel & Mobile) and, secondary organic aerosols type 2 (SOA_2) with origins ranging from mainly regional to mainly local. Factors that were mainly local (PTOM, Steel & Mobile, SOA_2) contributed up to 17% of the average PM 2.5 mass while mixed local/regional factors (pNO3, pSO4) made up 43% on average, indicating the potential for further reduction of harmful PM concentrations locally. Of particular interest from a health protection perspective, was the composition of PM 2.5 on days when an exceedance of the 24-hr WHO air quality guideline for this pollutant was observed. In general, SOA_1 was found to drive summer exceedances while pNO3 dominated in the winter. During the summer period, SOA_1 was attributable to wildfires in the northern parts of Canada while local traffic sources in winter contributed to the high levels of pNO3. While local, industrial factors only had minor relative mass contributions during exceedances, they are high in highly oxidized organic species (SOA_2) and toxic metals (Steel & Mobile). Thus, they are likely to have more impacts on human health. The methods and results described in this work will be useful in understanding prevalent sources of particulate matter pollution in the ambient air in the presence of complex topography and meteorological effects. [Display omitted] • DN-MT-FA apportioned sources of PM 2.5 in a city with complex topography. • Dispersion-normalization helps to understand local/regional origins of factors. • Industrially sourced factors had most PM 2.5 metals and unique organic species. • Summer exceedance of WHO AQG for PM 2.5 mainly driven by secondary organic aerosols. • Winter exceedance of WHO AQG for PM 2.5 largely driven by particulate nitrate. [ABSTRACT FROM AUTHOR]